… classification report. Results Among the four models, the AUC value of support vector machine
was … by support vector machine, each index was equal to the average value of the model. …

… waveband combination from 240 wavebands … support vector machines as a classifier for
the identification of maximally-effective waveband combination.Results: A binary classification …

… In this study, a hippocampal subfield segmentation approach based on CNN and support
vector machine (SVM) is … Brain tumor segmentation using convolutional neural networks in MRI …

… Nurtanio 等[2]采用支持向 量机(support vector machine,SVM)实现了对囊肿与 肿瘤病变的
分类,结果表明囊肿与肿瘤病变的鉴 别准确率可达87.18%,受试者工作特征曲线下面 积可达0.94.DL …

… 人工智能经过推理期,知识期,机器 学习期和深度学习期4 个阶段,以人工神经网 络(artificial
neural network,ANN),支持向量机 (support vector machine,SVM)及卷积神经网络 (convolutional …

… to study brain tumor grading problem with BRATS2017 open datasets. Results: A complete
… 临床结论的预测模型,支 持向量机(support vector machine,SVM)[19]就是最 常用的分类器之一. …

… Automatic detection and classification of nasopharyngeal carcinoma on PET/CT with
support vector machine[J]. Int J Comput Assist Radiol Surg, 2012, 7(4): 635-646. doi:10.1007/…

… different wavelet transforms and support vector machines[C]// … sification of brain tumor
using support vector machine based … A Fully automated deep learning network for brain tumor …

… Fully automatic segmentation of brain tumor images using support vector machine classification
… [C]//International Conference on Medical Image Computing and Computer-Assisted Inter…

… Note: LDA is linear discriminant model; QDA is quadratic discriminant model; RF is random
forest model; SVM is support vector machine model; BP is error back propagation model; …